Method and System for Recording Recommended Content Within a User Device

ABSTRACT

A user device and method for operating the same includes a memory and a controller that stores an external recommendation list in the memory, said external recommendations list comprising a marketing list comprising a plurality of marketing list entries and a related program list comprising a plurality of related program entries that are related to the plurality of marketing list entries. Each marketing list entry has a related score corresponding to a respective marketing list entry. The controller generates a most viewed programming list, comparing the external recommendations list and most viewed programming list using the related score and generates a recommended recording list using both the external recommendation list and the most viewed programming list. The controller also stores at least one content from the recording recommendation list in the memory.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.13/803,395, filed on Mar. 14, 2013, which is a continuation-in-part ofU.S. application Ser. No. 13/529,040, filed on Jun. 21, 2012 and claimspriority to U.S. Provisional Application 61/500,855, filed on Jun. 24,2011. The entire disclosures of the above applications are incorporatedherein by reference.

TECHNICAL FIELD

The present disclosure relates generally to providing recommendationsfor content users, and, more specifically, to a method and system forautomatically recording content based on recommendations from a contentrecommendation system without further user interaction.

BACKGROUND

The statements in this section merely provide background informationrelated to the present disclosure and may not constitute prior art.

Television programming content providers are increasingly providing awide variety of content to consumers. Available content is typicallydisplayed to the user using a grid guide. The grid guide typicallyincludes channels and timeslots as well as programming information foreach information timeslot. The programming information may include thecontent title and other identifiers such as actor information and thelike.

Because the number of channels is so great, all of the channels cannotbe simultaneously displayed on the screen display. A user can scroll upand down and sideways to see various portions of the program guide fordifferent times and channels. Because of the large number of contenttitles, and timeslots and channels, is often difficult to decide on aprogram selection to view.

In a typical content providing system, a user must preschedule contentto be recorded within a user device. If the content is broadcastedwithout the user scheduling a recording, the content may forever beunavailable to the user.

SUMMARY

The present disclosure provides a system and method for generatingrecommendations and automatically recording at least some of therecommendations in the user device without further user interaction.

In one aspect of the disclosure, a method includes generating anexternal recommendation list at a head end, communicating the externalrecommendation list to a user device, generating a most viewedprogramming list, generating a recommend recording list based on theexternal recommendation list and the most viewed programming list andstoring at least one content from the recording recommendation list atthe user device.

In a further aspect of the disclosure, a user device includes a memoryand a controller storing an external recommendation list received from ahead end in the memory. The controller generates a most viewedprogramming list and generates a recommend recording list based on theexternal recommendation list and the most viewed programming list. Thecontroller stores at least one content from the recording recommendationlist in the memory.

Further areas of applicability will become apparent from the descriptionprovided herein. It should be understood that the description andspecific examples are intended for purposes of illustration only and arenot intended to limit the scope of the present disclosure.

DRAWINGS

The drawings described herein are for illustration purposes only and arenot intended to limit the scope of the present disclosure in any way.

FIG. 1 is a high level block diagrammatic view of a recommendationsystem according to the present disclosure.

FIG. 2 is a block diagrammatic view of the user device of FIG. 1.

FIG. 3 is a simplified block diagrammatic view of the recommendationsmodule according to the present disclosure.

FIG. 4 is a flowchart of a method for forming a viewer tracking log.

FIG. 5 is a channel versus time plot of channel changes for an exampleof a user device operating.

FIG. 6 is a table of the channel tune events corresponding to the plotof FIG. 5.

FIG. 7 is a channel tune time calculation table having various tunetimes for the various programs.

FIG. 8 is a simplified view of recommendations provided by therecommendations engine for a What's On portion and a You Might Likeportion.

FIG. 9 is a flowchart of a simplified method for generating the What'sOn list and the You Might Like list.

FIG. 10 is a flowchart of a method for generating a What's On list.

FIG. 11 is a flowchart of a method for generating a You Might Like list.

FIG. 12 is a flowchart of a method for determining the timeslot.

FIG. 13A is a method for generating the most watched channels bytimeslot list.

FIG. 13B is a flowchart for generating the timeslot viewer preferredchannels list.

FIG. 14 is a flowchart of a method for generating the related channelslist.

FIG. 15 is a flowchart of a method for generating a timeslot seriesprofile.

FIG. 16 is a flowchart of a method for generating the timeslot seriesprofile match.

FIG. 17 is a flowchart of a method for generating a genre match.

FIG. 18 is a vector representation of a genre match example.

FIG. 19 is a table corresponding to the genre match algorithm for theexample of FIG. 18.

FIG. 20 is a table illustrating the adjusting of genre weights inresponse to a watched program event.

FIG. 21 is a flowchart of a method for adjusting genre weights inresponse to a watched program event.

FIG. 22 is a table for the set top box viewer tracker log.

FIG. 23 is the program guide data associated with the example for FIG.22.

FIG. 24 is an example of program guide data for a new set top box.

FIG. 25 is a flow chart for a method of generating an externalrecommendation list.

FIG. 26 is a table illustrating an example of a marketing list.

FIG. 27 is a table illustrating a related program list.

FIG. 28 is a flow chart of a method for maintaining a series list.

FIG. 29 is a flow chart of a method for storing content in the userdevice.

FIG. 30 is a front view of a user device.

FIG. 31 is a screen display of a memory space indicator.

FIG. 32 is a flow chart of a method for changing a screen display.

FIG. 33 is a flow chart of a method for displaying indicators accordingto the present disclosure.

FIG. 34A is a screen display illustrating an entry screen forintroducing a recommendation recording system.

FIG. 34B is a screen display for enabling the recording recommendationsystem.

FIG. 35 is a screen display illustrating “What's On” and recordingrecorded recommendations.

FIG. 36 is a screen display illustrating the result of a contentselection from FIG. 35 and related content.

FIG. 37 is a screen display for recording a series.

FIG. 38 is a detailed screen display of recommended recording content.

FIG. 39 is a screen display illustrating recorded content correspondingto a selected series.

FIG. 40 is a screen display for removing a series from the recordedrecommendation list.

FIG. 41 is a screen display for confirming a series recommendationremoval.

DETAILED DESCRIPTION

The following description is merely exemplary in nature and is notintended to limit the present disclosure, application, or uses. Forpurposes of clarity, the same reference numbers will be used in thedrawings to identify similar elements. As used herein, the term modulerefers to an application specific integrated circuit (ASIC), anelectronic circuit, a processor (shared, dedicated, or group) and memorythat execute one or more software or firmware programs, a combinationallogic circuit, and/or other suitable components that provide thedescribed functionality. As used herein, the phrase at least one of A,B, and C should be construed to mean a logical (A or B or C), using anon-exclusive logical OR. It should be understood that steps within amethod may be executed in different order without altering theprinciples of the present disclosure.

The teachings of the present disclosure can be implemented in a systemfor communicating content to an end user or user device. Both the datasource and the user device may be formed using a general computingdevice having a memory or other data storage for incoming and outgoingdata. The memory may comprise but is not limited to a hard drive, FLASH,RAM, PROM, EEPROM, ROM phase-change memory or other discrete memorycomponents.

Each general purpose computing device may be implemented in analogcircuitry, digital circuitry or combinations thereof. Further, thecomputing device may include a microprocessor or microcontroller thatperforms instructions to carry out the steps performed by the varioussystem components.

A content or service provider is also described. A content or serviceprovider is a provider of data to the end user. The service provider,for example, may provide data corresponding to the content such asmetadata as well as the actual content in a data stream or signal. Thecontent or service provider may include a general purpose computingdevice, communication components, network interfaces and otherassociated circuitry to allow communication with various other devicesin the system.

Further, while the following disclosure is made with respect to thedelivery of video (e.g., television (TV), movies, music videos, etc.),it should be understood that the systems and methods disclosed hereincould also be used for delivery of any media content type, for example,audio, music, data files, web pages, advertising, etc. Additionally,throughout this disclosure reference is made to data, content,information, programs, movie trailers, movies, advertising, assets,video data, etc., however, it will be readily apparent to persons ofordinary skill in the art that these terms are substantially equivalentin reference to the example systems and/or methods disclosed herein. Asused herein, the term title will be used to refer to, for example, amovie itself and not the name of the movie. As used herein, the contentwill be used to refer to, for example, a movie or program itself.Content identifier refers to the data associated with content used foridentifying the content. Machines may use an actual numeric oralphanumeric value unique to the content. People may use a title foridentification. Both types and other types of data may be associatedwith the content for association. For program guides and recommendationslist content identifiers, a cluster identifier and other data may alsobe provided with the content.

While the following disclosure is made with respect to example DIRECTV®broadcast services and systems, it should be understood that many otherdelivery systems are readily applicable to disclosed systems andmethods. Such systems include wireless terrestrial distribution systems,wired or cable distribution systems, cable television distributionsystems, Ultra High Frequency (UHF)/Very High Frequency (VHF) radiofrequency systems or other terrestrial broadcast systems (e.g.,Multi-channel Multi-point Distribution System (MMDS), Local Multi-pointDistribution System (LMDS), etc.), Internet-based distribution systems,cellular distribution systems, power-line broadcast systems, anypoint-to-point and/or multicast Internet Protocol (IP) delivery network,and fiber optic networks. Further, the different functions collectivelyallocated among a service provider and integrated receiver/decoders(IRDs) as described below can be reallocated as desired withoutdeparting from the intended scope of the present patent.

In the following examples, recommendations of titles of various programsare provided. The content recommendations may provide a title eithergraphically or alpha-numerically or a combination of both. Graphically,content posters or thumbnails may be provided. Several lists aregenerated, sorted and processed herein. The lists may include content orprogram titles or one or more alphanumeric identifiers or both. The listmay not contain the actual content itself.

Referring now to FIG. 1, a satellite television broadcasting system 10is illustrated. The satellite television broadcast system 10 includes ahead end 12 that generates wireless signals 13 through an antenna 14which are received by an antenna 16 of a satellite 18. The wirelesssignals 13, for example, may be digital. The wireless signals 13 may bereferred to as an uplink signal. A transmitting antenna 20 generatesdownlink signals that are directed to various receiving systemsincluding stationary systems such as those in the home, as well as,mobile receiving systems. As is illustrated the receiving systems arereferred to as a set top box or user device 22. Each user device 22 isin communication with a respective antenna 24. Each antenna 24 receivesdownlink signals 26 from the transmitting antenna 20 of the satellite18. Thus, the user devices may be referred to as satellite televisionreceiving devices.

The head end 12 may communicate various content 30 or program guide data32 through the satellite 18. The user device 22 may receive the content30 and program guide data 32 for use therein. The head end 12 may alsoinclude a recommendation authoring system 34. The recommendationauthority system 34 generates an external recommendation list that isultimately communicated to each of the user devices. The externalrecommendation list may include recommended content titles, relatedcontent to the recommended content and the strength of similarity scorebetween the related content and recommended content. In this case boththe recommended content and the related content refer to content titlesfor the specific programming. The external recommendation list mayinclude other types of metadata such as the channel, actors, ratings,the start and end times, the date and information as to whether thecontent will be broadcasted at a different time. In the present example,the external recommendation list is the same for each of the user device22. As will be described below the external recommendation list may becommunicated to and modified by the user devices 22.

The recommendation authoring system 34 may be a combination of automatedand operator controlled systems. The recommendation authoring system 34may receive data from various sources including external sources 35 andinternal sources 37 available from within the head end. The externalsources 35 may, for example, be provided from one or more experts, fromNielsen® ratings, Blue Fin®, or other external sources. An example ofinternal sources is “What's Hot” which is a list of the most watched andtalked about programming available from the system provider associatedwith the head end 12. The internal sources 37 may also be modifiedaccording to various marketing experts within the head end. Thecompilation of the external sources and internal sources may beperformed to obtain the external recommendation list. Both the externalsources 35 and internal sources 37 may also generate the related contentlist. The related content list may also have the same type of metadataassociated with the recommended content.

The recommendation authority system 34 may change the content of theexternal recommendation list converted into a binary format of datafiles for communication into the user devices. The binary format datafile may be included with payload object and communicated to the varioususer devices. This process will be described in more detail below.

The user devices 22 may be in communication with the head end 12 througha network 36. The network 36 may be one type of network or multipletypes of networks. The network 36 may, for example, be a public switchedtelephone network, the internet, a mobile telephone network or othertype of network.

User devices 22 illustrated in FIG. 1 may be interconnected within ahousehold, multi-dwelling unit or commercial building. User devices 22may be inter-connected through a local network (not illustrated) such asa wireless network or a wired network. The interconnection of the userdevices 22 may allow for multi-room viewing of content as well ascoordinated content recording. That is, content stored on one set topbox may be communicated to another set top box through the network.

A mobile device 40 may also be incorporated in the system 10. The mobiledevice 40 may also receive downlink signals from the satellite 18. Themobile device 40 may also be in communication through a wireless networkto the head end 12.

The network 36 may also be in communication with a home media center 50.The home media center 50 may be in communication with a plurality ofclient devices 52. The client devices 52 may be set top boxes or otherclients such as an RVU® client. Thus, the home media center 50 may haveone central storage device therein. The home media center 50 may be usedto distribute content, channels, programs and other data to each of theclient devices 52. The home media center 50 may also include an antenna24 for communicating with the satellite 18 in a similar manner to thatillustrated above with respect to the user devices 22.

Referring now to FIG. 2, a user device 22, such as a set top box isillustrated in further detail. Although, a particular configuration ofthe user device 22 is illustrated, it is merely representative ofvarious electronic devices with an internal controller used as a contentreceiving device. The antenna 24 may be one of a number of differenttypes of antennas that includes one or more low noise blocks. Theantenna 24 may be a single antenna 24 used for satellite televisionreception. The user device 22 may be coupled to a display 110. Thedisplay 110 may have an output driver 112 within the user device 22. Amobile device such as that described above may have an omni-directionalantenna.

A controller 114 may be a general processor such as a microprocessorthat cooperates with control software. The controller 114 may be used tocoordinate and control the various functions of the user device 22.These functions may include a tuner 120, a demodulator 122, a decoder124 such as a forward error correction decoder and any buffer or otherfunctions. The controller 114 may also be used to control the storing ofan external recommendations list within the memory of the controller,automatically storing recommended content, storing user requestedcontent in the memory, and comparing selections to already storedcontent.

The controller 114 may also include a viewer tracking module 116, arecommendation module 118 and a display suppression module 119. Theviewer tracking module 116 is used for tracking and logging viewingevents at the user device 22. Ultimately, the viewer history may belogged in a viewer tracking log as will be further described below. Theviewer tracking module 116 may track the time a content was watched, thetitle of the content and if the content belongs to a series. Therecommendation module 118 is used for generating recommendationscorresponding to programs currently available for viewing correspondingto previously watched content during a particular timeslot. Therecommendation module 118 may also generate programs or recordings thatare deemed to be future or current programming that the viewer shouldlike based on an analysis of viewing habits of the viewer. Therecommendations module 118 may receive the external recommendationslist. Both types of recommendations will be further described below.

The controller 114 may also include a display suppression module 119.The display suppression module 119 is used to suppress the display ofvarious data. In the present example the data suppressed may includesuppressing the recommended content from appearing in the amount ofavailable space within a memory. That is, the capacity of the userdevice may appear greater than is actually available. For example, amemory space indicator may be displayed on the display 110. Contentrecorded from the recommended recording list may be stored in the memory130 without being accounted for therein. This will allow the memoryspace indicator to indicate to the user that more space is available.The content stored from the recommended recording list may thus beremoved or replaced when a user attempts to record user-requestedprogramming therein. The display suppression module 119 may alsosuppress the display of a recording indicator 121 that that content isbeing recorded by the user device 22. The recording indicator 121 may bean LED on the external surface of the user device 22 that is illuminatedwhen content is being recorded. The recoding indicator 121 may not beilluminated when content is automatically recorded using the recommendedrecording list. This will make it appear to a user that the system isfully capable to perform any user-generated requests.

The tuner 120 receives the signal or data from the individual channel.The tuner 120 may receive television programming content, program guidedata or other types of data. The demodulator 122 demodulates the signalor data to form a demodulated signal or data. The decoder 124 decodesthe demodulated signal to form decoded data or a decoded signal. Thecontroller 114 may be similar to that found in current DIRECTV® set topboxes which uses a chip-based multifunctional controller. Although onlyone tuner 120, one demodulator 122 and one decoder 124 are illustrated,multiple tuners, demodulators and decoders may be provided within asingle user device 22.

The controller 114 is in communication with a memory 130. The memory 130is illustrated as a single box with multiple boxes therein. The memory130 may actually be a plurality of different types of memory includingthe hard drive, a flash drive and various other types of memory. Thedifferent boxes represented in the memory 130 may be other types ofmemory or sections of different types of memory. The memory 130 may benon-volatile memory or volatile memory.

The memory 130 may include storage for various operational datacollected during operation of the user device 22. One type of datastorage includes the viewer tracking log 132 obtained and controlled bythe viewer tracking module 116. The viewer tracking log (VTL) 132includes viewer tracking log data that includes data about details ofprograms that have been watched or played back, including what time thatthey were watched or played back. The data of the VTL 132 may alsoinclude how long they were watched and program details. The programdetails may include whether the program belongs to a series. Recordingdeletion data within a digital video recorder may also be included inthe data of the VTL 132.

Another type of memory 130 is the settings and the list information(SLI) memory 134. The SLI memory 134 may store various types of dataincluding set top box playlist data 136 that has the playlist forcontent saved within the user device 22. The playlist data containscontent visible to users and content currently non-visible to users.Another type of data is the favorite settings for the user device 22.The favorites may be stored in a favorite's memory 138. Other types ofdata may also be included in the SLI memory 134 which is illustrated asan “other” data memory 140. The other data memory 140 may includevarious types of data including ignored suggestions which correspond tosuggestion or recommendation suggestions that were ignored. Another typeof data in the other data memory 140 may include the channelsubscription data, the blocked channels, adult channels, rating limitsset by the user device 22, current set top box language, prioritizerdata, TV resolution data, to do list data, the conditional access moduleidentifier, and a request identifier. The request identifier may begenerated at the simulation engine 50 of FIG. 1 as is further describedbelow. Further, time zone data, time of day daylight savings, statusdata, aspect ratio data, viewing hours data, quick tune list and a zipcode may all be included within the other memory 140 of the SLI memory134.

The memory 130 may also include advanced program guide memory 144. Theadvanced program guide (APG) memory 144 may store program guide datathat is received within the system. The program guide data may storevarious amounts of data including two or more weeks worth of programguide data. The program guide data from the APG memory 144 may becommunicated in various manners including through the satellite 18 ofFIG. 1. The program guide data may include a content or programidentifiers, and various data objects corresponding thereto. The contentidentifier may include series data. The first 4 digits may, for example,identify the series. The program guide may include programcharacteristics for each program content. The program characteristic mayinclude ratings, categories, actor, director, writer, content identifierand producer data. The data may also include various other settings.

The memory 130 may also include a digital video recorder 146. Thedigital video recorder 146 may be a hard drive, flash drive, or othermemory device. A record of the content stored in the digital videorecorder is a playlist. The playlist may be stored in the DVR 146 or aseparate memory as illustrated.

The digital video recorder 146 may include a user partition 148 and anetwork partition 149. The network partition 149 is a portion of thememory used for storing various operating conditions, and to pushcontent that may be provided to the user. Typically the networkpartition part of the DVR memory 146 is relatively small compared to theuser partition 148. The user partition 148 is typically controlled bythe user. The user partition 148 is used for storing content requestedto be stored by the user. The digital video recorder 146 stores contentupon request by the users through various types of interfaces. Userrequests for recording may also be communicated from a remote system.The user partition 148 as will be described further below, may be usedfor storing content from the recommended recording list withoutinteraction with the user. That is, content may be automatically storedwithin the user partition 148 as determined by the recommended recordinglist. This content may have an extremely low priority and thus the usermay overwrite the contents automatically stored within the memory. Asmentioned above, the display suppression module 119 may suppress atleast a portion of the displays. The display suppression module 119 maysuppress the content stored in response to the recommended recordinglist within the user partition 148 so that the user partition does notappear to be fuller than the recordings requested by the user. Thisprocess will be described in further detail below.

The user device 22 may also include a user interface 150. The userinterface 150 may be various types of user interfaces such as akeyboard, push buttons, a touch screen, a voice activated interface orthe like. The user interface 150 may be used to select a channel, selectvarious information, change the volume, change the display appearance,or other functions. The user interface 150 may also be used forselecting recommendation and providing feedback for recommendations aswill be described below. The user interface 150 may thus be used forgenerating a selection signal.

A network interface 152 may be included within the user device 22 tocommunicate various data through the network 36 illustrated above. Thenetwork interface 152 may be a WiFi, WiMax, WiMax mobile, wireless,cellular, or other types of communication systems. The network interface152 may use various protocols for communication therethrough including,but not limited to, hypertext transfer protocol (HTTP).

Referring now to FIG. 3, the recommendation module 118 and itsinter-connections are illustrated in further detail. The recommendationmodule 118 is in communication with the viewer tracking module 116. Theviewer tracking module 116 includes a viewer events module 210 which isin communication with a tracker module 212 which in turn is incommunication with a viewing tracker log 214. The viewing tracker log214 may ultimately be stored in the memory of the user device asillustrated in FIG. 2. A most viewed programming list may be stored inthe viewing tracker log.

The viewer events module 210 generates data corresponding to viewingevents so that the recommendation module 118 is able to generate usefulrecommendations likely to be of interest to the user. Various viewingevents may include tuning to live television events, playing backrecordings, channel changes and trickplay changes. Trickplay changes mayinclude various digital video recorder functions including skippingvarious content during playback, or other digital video recorderfunctions.

The live viewing events may only be logged after a predetermined amountof time has passed while viewing a channel. A live viewing event maytherefore have a time the tuning change occurred (which is the time theevent was generated minus the 30-second waiting period), the channelobject of the channel tuned and a program object of the programcurrently airing. Other information in the live viewing data may includea dual-live buffer swap.

A live television viewing event may also be generated when the currentprogram ends and another begins in order to note the change of theprogram object identifier. In such a case, the event may be immediatelygenerated with no 30-second lag between the change and the generation ofthe event.

A playback viewing event may also be logged. The playback of a programfrom a digital video recorder may be a playback viewing event. The timethe playback began (which is the time the event was generated minus the30-second waiting period), the channel object of the channel that therecording was recorded from and the program object of the recording mayall be recorded.

A channel change may also be logged by the viewer events module 210. Ifthe viewer changes the channel that is currently being viewed live, achannel change event may be logged. The time the channel was changed,the original channel and the destination channel may be logged.

Trickplay changes may also be monitored. If a trickplay is performed andno other trickplays are performed within a predetermined amount of time,the trickplay event may be logged. The time the trickplay change occurs,the location that the trickplay occurs within the recording and the newtrickplay state may all be logged.

An idle-mode change may also be logged. That is, if the set top box oruser device goes into an idle mode or comes out of an idle mode, an idlemode change event may be logged. The time the idle mode change occurred,a flag indicating whether the user device is entering or exiting an idlemode and a flag indicating whether the idle mode is actually stand-by,may all be logged.

An audio change is another viewer event that may be logged. If theviewer changes audio on the currently-tuned channel or in a recording,then an audio change event may be logged. The time the audio changeoccurred, a new audio stream identifier and an audio stream language mayall be logged.

The viewer event module 210 may also log whether a recording has beendeleted. If a recording has been deleted from the digital videorecorder, a recording deleted event may be logged. The recording deletedevent may include the time the recording was deleted, the channel objectof the channel that the recording being deleted was from, the programobject of the recording deleted and the reason the recording was deletedsuch as an explicit viewer deletion, a recording expiration, no room onthe hard drive or the like.

The various types of events mentioned above may be used to generate amost viewed programming list. The most viewed programming list mayinclude the most viewed series from the various types of viewing eventssuch as live television, playback viewing, channel changes and quickplay and the like. The series within the most viewed programming listmay ultimately be used to generate a recommended recording list. Therecommended recording list may be generated from a correlation of themost viewed programming list and the external recommendation list withinthe correlation module 224. In one example that will be described morebelow, the correlation module 224 may review the external recommendationbut to determine if any series on the most viewed programming list areon the external recommendation list. Matching content may be used toform the recommended wordings list 246.

The viewer events from the viewer events module 210 are communicated tothe tracker module 212 which gathers the viewer events, analyzes themand based on the analysis adds the entries to the viewer tracking log214. The viewer tracking log 214 may include the watched programs andrecordings deleted.

The tracker module 212 may include a viewing tracker module queue 220that queues the various viewer events. An aggregate queued events module222 may aggregate the queued events and store them within the viewingtracker log 214.

The viewer tracking module 116 may be specific to one user device in asystem such as a networked system illustrated in FIG. 1. The home mediacenter 50 may keep track of data individually for each client. The homemedia center 50 could also be configured to aggregate data such as mostchannels watched, the viewer tracking log and other data.

The recommendation module 118 may also be in communication with set topbox specific information 230 including the playlist and the channelssubscribed to. These may be referred to as “channels I get.”

The recommendation module 118 may also be in communication with thecurrent program guide data 232. The program guide data 232 correspondsto the currently available programs provided by the head end.

The recommendation module 118 may also be in communication withsupplemental guide data 234. The data 234 corresponds to various dataobjects that may be sent together with the program guide data. Thesupplemental guide data 234 may include channels recommended. Therecommended channels may be recommended by a person or determined bymachine. The channels recommended may be communicated from the head end12 as a data object to the user device 22. The recommended channels maybe in a list from most recommended to least recommended.

Outside sources may also provide data. Outside sources may includesources that provide recommended programs. For example, programs may berecommended based upon a selection. Thus, all recommended programsrelated to a selected program may be provided. A list of relatedtelevision series related to a selected television series may also beprovided. The recommendations may be performed based upon various objectdata. The supplemental data may also include a channel group whichgroups channels together. For example, related channels may be groupedtogether based upon content typically played at such channels. A dailyeditorial list may also provide data selected by a person or a machinefor a particular time period. For example, if a certain sporting eventsuch as the Super Bowl will be played that day, this may be includedwithin the daily editorial list. Other special events for a particularday may also be included within the daily editorial list. The dailyeditorial list is an example of an external recommendation list.

A filter module 236 for filtering available content may also be used.The filter module 236 may include the watched program ratings, channellocks, adult content filters or other user selectable filters. Thefilters prevent content titles from appearing in the recommendationslists.

The recommendation module 118 may generate an output to a display 240.The output is a recommendations list having titles, poster or otheridentifiers of content that may be desirable for the user. In thepresent example a first recommendation list and a second recommendationlist is displayed simultaneously. Each list is generated using adifferent method. The display 240 may include a What's On display 242 asthe first recommendation list and a You Might Like display 244 as thesecond recommendation list. The output may be in graphical,alphanumeric, or a combination of graphical and alphanumericidentifiers. These passages will be further described below.

Another type of list may also be generated such as a recommendedrecordings list 246. The recommended recordings list 246 may replace theYou Might Like list 244 if the user opts into this feature. Therecommended recordings list 246 may display recommended recordingsrecorded within the user partition of the digital video recorder. Thiscontent will be available without delay so that downloading delays arenot experienced by the user. In one example, the What's Onrecommendation list 242 for items that are currently being broadcastedmay be displayed on a split screen with the recommended recordings list246. Of course, the first few items of the What's On list and recordedrecommendation list 246 may be displayed. If the user through the use ofa user interface requires further contents on the list the contents maybe scrolled as will be described further below.

Referring now to FIG. 4, a method for determining whether a program waswatched live or a recording was watched is set forth. In step 310, theidle mode change events are stored. Further, whether the user device isin an idle mode is stored. In step 312, channel change events arestored. In step 314, it is determined whether a timeslot has beenchanged. If a timeslot has changed in step 314, the unique programs arestored in step 316. After step 316, the total time watched for eachprogram is stored. This may be performed by calculating the time asegment of a program was watched by calculating the delta from the timeof a live television viewing or playback viewing event at the time ofthe next live television viewing or playback event or the time of thenext channel change event. This is performed in step 318. In step 320,the time that the set top box was in idle mode is subtracted from eachsegment in step 320. In step 322, any fast-forward trickplay modes arealso subtracted.

In step 324, all the segments of the same program are summed together.In step 326, not all of the events may be stored in a viewer log. Thisreduces the size of the viewer log to a manageable size. In this case,20% of a timeslot is used. Thus, if the sum of all the segments in atimeslot is greater than 20% of the timeslot in step 326, the viewerevent is added to the viewer log in step 328. In this case, a timeslotmay be 30 minutes and thus the 20% corresponds to six minutes. Ofcourse, other times may be used. The 20% is merely used as anon-limiting example. In step 326, if the sum of all the programsegments does not total 20%, then step 330 does not add the program tothe viewer log.

A timeslot is a predefined time period having a start time and an endtime. For example, a timeslot may be 7:00 p.m. to 7:30 p.m. If thepresent time is 7:15 p.m., 7:00 to 7:30 p.m. is the current timeslot and7:30 p.m. to 8:00 p.m. is the next timeslot.

Referring now to FIG. 5, an example of a channel usage event during atimeslot is set forth. In this example, the timeslot is 30 minutes.However, various other timeslots may be used. The timeslot for arecording may be different than a live event such as 60 minutes. In thisexample, four channels A, B, C, D are used. For the first segmentbetween 0 and 1.5 minutes, channel A or program P1 is watched. In thesecond segment, channel B is tuned to program 2 (P2). The second segmentcontinues from 1.5 minutes through 6 minutes. The channel is thenchanged to channel C, then to channel D, then back to channel B. Thisoccurs between minutes 6 and 7. Between minutes 7 and 9.5, channel Bprogram P2 is tuned. At time 9.5 minutes, the channel is tuned toprogram A until 15.5 minutes. At 15.5 minutes, channel D, program P3 waswatched for one minute. The channel was then returned to channel Bprogram 2 until 25 minutes. At the 25-minute time period, channel Bswitched programs to program P4.

Referring now to FIG. 6, the viewer tracking module receives the eventset forth in the table illustrated therein. The live tuning events setforth in the table are limited by the threshold period. The tuning tochannels C and D at the 6-minute mark do not result in a live televisiontuning event since their period is shorter than the 30-second timethreshold. The tuning event at channel B at the 25-minute mark with nochannel change occurs because the program changed from program P2 toprogram P4.

Referring now to FIG. 7, a channel tune time calculation table isillustrated. The programs are sorted and the viewer tracking log obtainsthe data within the table. From this table, it can be determined thatprogram P1 was watched for 7 minutes and 30 seconds total. Program P2 onchannel B was watched for 15 minutes and 45 seconds while program P3 onchannel D was watched for 1 minute and program P4 on channel B waswatched for 5 minutes. The programs P3 and P4 do not meet the minimum6-minute time and thus will be discarded in the viewer tracking log.Consequently, program P1 on channel A will be logged for 7 minutes and30 second and program P2 on channel B will be logged for 15 minutes and45 seconds in the viewer tracker log.

Referring now to FIG. 8, one example of the recommendation processresults is a recommendation screen 410 which is broken down into aWhat's On portion 412 and a You Might Like portion 414. The What's Onprogram list has program content titles for programs that are regularlywatched during a current timeslot. The program content in the What's Onlist is content that is currently being broadcast. The What's On listmay include a plurality of thumbnails for 416, 418, 420, and 422. Analphanumeric list may also be provided in addition to or in place of thethumbnails. The television or display associated with the set top boxmay be directly tuned by selecting one of the thumbnails 416-422 usingthe user interface.

The You Might Like portion 414 lists recommendations for the viewer. TheYou Might Like portions are programs that are not regularly watched byusers. The You Might Like recommendations can be available now or infuture. A plurality of thumbnails 424-430 is provided. The thumbnails424-430 displayed in the You Might Like portion 414 correspond torecommendations from the recommendation engine.

The viewer-tracking and recommendation algorithms described hereinoperate in the satellite-connected set top box with or without a networkconnection or feedback from the set top box to the head-end. Feedbackmay be provided from broadband-connected set top box users, to enable PCor mobile users to log in to their account and view theirrecommendations. The feedback may also allow analysis and improvement ofthe performance of the recommendation algorithms.

Referring now to FIG. 9, a high-level flowchart of the process is setforth. In step 910, when a viewer event is generated, step 912 outputsthe viewer event to the viewer tracking module. From the viewer trackingmodule, a tracking log is generated in step 914. In step 918, a list ofrecommendations for the What's On and the You Might Like screen displaysbased upon the viewer tracking log is obtained. In step 920, other datais obtained by the system to populate the What's On and the You MightLike screen display. Further details of this method are set forth below.

Referring now to FIG. 10, a method for generating the What's On list ofrecommendations at the recommendation engine is set forth. In general,the method uses viewing habits at the user device to provide appropriaterecommendations. As will be described below, when the viewing habits donot provide enough information to fill up a list, other sources of datamay be used.

In step 1010, a current timeslot is determined. A current timeslot isdetermined in order to analyze the programs and channels normally viewedat that time of day or day of week. The current timeslot is used togenerate recommendations that are relevant to the viewers that normallyview television at that time of day or week. A current timeslot enablesrecommendations to be generated for a shared television based ondifferent viewers and different viewing habits at different timeslots.Determining the current timeslot will be further set forth below. Ingeneral, the current timeslot for the present example is 30 minutes.Thus, data will be analyzed for the current 30-minute timeslot. The nexttimeslot may also be used depending on the relative time within thetimeslot. The choosing of the timeslot will be described further in FIG.12.

In step 1012, a timeslot viewing profile generation algorithm is used todefine a timeslot viewing profile for programs viewed live and forrecordings played back during the current timeslot. The timeslot viewingprofile may identify a program series. In such a case, the profile maybe referred to as a timeslot series profile. A series is a program titlethat has multiple episodes. Traditionally, a series runs consecutiveweeks on a network. Although many networks offer repeats of varioustimes. Again, the timeslot series will be described further below inFIG. 15. It should be noted that the timeslot for playback recordingsversus live television may be different. For example, live recordingsmay have 30-minute timeslots while live recordings may have 60-minutetimeslots. Of course, the timeslots may both be the same. The timeslotseries profile may return a plurality of content titles for series mostwatched within a timeslot. In step 1014, the timeslot viewing profile ismatched against currently available content in the program guide. Theseries identifier in the content identifier may be compared to a seriesidentifier of available content in the program guide. The list obtainedduring matching is used to populate the What's On list.

In step 1016, it is determined whether or not the What's On list isfull. If the What's On list is full in step 1018, the list is displayed.As described above, the list may be displayed in a thumbnail, a poster,an alphanumeric display, or combination thereof.

Referring back to step 1016, if the list is not full, additionalrecommendations for the list may be obtained. In step 1020, a timeslotviewer preferred channels list may be developed. The timeslot viewerpreferred channels list returns a list of preferred channels or typicalchannels watched during the timeslot of interest. The list provides ascore or ranking value for each channel to provide a relative indicationof importance or usage. More popular channels will be ranked higher. Instep 1022 select the current programs from the timeslot viewer preferredchannels list. In step 1024, a genre match algorithm based upon theviewer preferred program genres may be used to provide a score orranking for programs from available content on the viewer preferredchannels in the timeslot that match the typical genre. Higher rankedchannels will be matched first. In step 1026, the highest rankingprogram matches are added to the What's On list. After step 1026, theWhat's On list is displayed on a display associated with a user device.The timeslot viewer preferred channels and genre-matching algorithm willbe described further below in FIGS. 13 and 17, respectively.

It should be noted that the algorithm for generating the What's On listmay have the contents filtered. That is, parental settings or ratingsettings may be set by the user at the user device. That is, adultcontent may not be added to the list if adult content is to be excluded.Likewise, content ratings higher than PG 13 may also not be added to thelist. Thus, at any point during the process, filters may be used toprevent content from being added to the What's On list.

Referring now to FIG. 11, a method for generating the You Might Likelist of recommendations are set forth. In step 1110, the What's On listfrom FIG. 10 is obtained. Thus, the What's On list provided from steps1010-1014 are used. Should additional features from steps 1020-1026 beinserted into the list, these may be added. In step 1112, similarprograms to those found in the What's On list are generated. Similarprogramming may be found using metadata or other types of data deliveredfrom the head end, as will be described below. The related program datamay be provided with the programming guide data. For example, data forrelated programs may be included in extended program objects of theprogram guide data. The related program data may be automaticallygenerated or inserted at various systems including the head end. Therelated program data may be received from external data sources. Therelated program data is such that when a viewer watches a program(either live or recorded), the related program data may be used as oneof the factors in predicting other programs content that the viewermight like. Related programs are determined in step 1112 for bothrecorded programs and those in the What's On list from FIG. 10.

In step 1114, related program titles that are already stored in the userdevice are eliminated. That is, the content identifier or program objectidentifier may be used to sort through the related list and eliminateidentical content. In step 1116, the first X number of content titlesfrom the reduced list may be used for the You Might Like list. The valueX may be chosen as 2 in the present example. However, various numbers ofrelated contents may be chosen.

In step 1118, if there is more space in the related or You Might Likelist, step 1120 is performed which obtains an editorial list. Theeditorial list is a list of content titles that may be set forth for atimeslot or other time period. The head end or external source maygenerate the list. The list may be a ranked list so the higher rankedcontent titles are compared first. In step 1122, a most watched channelslist is generated. In step 1124, the editorial list is compared to themost watched channels list. That is, if any of the editorial listprograms are on the most watched channels, step 1126 adds the programtitle or content identifier from the editorial list to the related orYou Might Like list. The editorial list may also include a targetchannels list with each content title such that the title may also beadded if any of the target channels is on the most watched channelslist. The editorial list may also include a list of related programs orseries with each content title such that the title may be added if anyof the related programs or series matches a regularly watched program orseries in the timeslot viewing profile generated in step 1012. Theeditorial list may also include a universal editorial content title,such that the title may be added for all viewers in a timeslot withoutchecking their most watched channels list. The process in steps1124-1126 is repeated until there is no more room in the You Might Likelist or the related list, or the maximum number of daily editorial listprograms has been added. Step 1128 determines whether the related or YouMight Like list is full. If the list is not full, step 1130 determineswhether the end of the editorial list or the maximum number of editorialitems has been added to the list. In one example, only two editoriallist matches may be added to the related or You Might Like list.

When the end of the editorial list or the maximum editorial entries hasnot been reached in step 1130, step 1122 is again performed. When theend of the editorial list or the maximum editorial entries has beenadded to the related list in step 1130, step 1134 seeks to add morecontent to the related or You Might Like list. Genre-matching may beused to obtain further items for the related or You Might Like list. Instep 1134, a related channels list is obtained. In step 1136,genre-matching may be applied to the upcoming programs on the relatedchannels. Genre-matching may be performed for the current timeslot aswell as a future timeslot. In step 1138, a list of matching programsfrom the related channels list is obtained. Values may be obtained forthe genre-matching of these programs. When a content title has a highestgenre match value or exceeds a minimum threshold corresponding to thehighest likelihood of a match, step 1140 adds the content title to therelated list. The closeness value is described below. If the relatedlist is not full in step 1142, step 1140 may add another content fromthe genre-matched related channels list. When the related or You MightLike list is obtained, step 1144 displays the You Might Like list withthe various content titles. The You Might Like list has a contentidentifier, a channel identifier and a program identifier associatedtherewith. However, only a thumbnail or alphanumeric descriptor may bedisplayed. The display may also be formed after steps 1118 and 1128 areperformed. That is, after there is no more room in the related list instep 1118 or the related list is full in step 1128, step 1144 isperformed.

Referring now to FIG. 12, as mentioned above, the timeslot of interestmust be determined. The timeslot used in the present example is 30minutes for live programming. The timeslot may be extended for recordedprogramming such as 60 minutes. Also, if the current timeslot is nearthe end of the timeslot, there is no sense in providing current timeslotinformation. Rather, the next timeslot information may be provided nearthe end of the timeslot.

In step 1210, if the current time is X minutes or more from the end ofthe current time period (which may be 30 minutes), step 1214 uses thecurrent timeslot. The value X may be five minutes or other appropriatesetting. In step 1210, when the current timeslot is not X minutes ormore from the end of the current time period, the next timeslot is usedin step 1212. That is, when the current time is closer than X minutes,step 1212 uses the next 30-minute timeslot for generatingrecommendations. The timeslot definition may be used in FIG. 10 which inturn is used in FIG. 11. Thus, both the What's On recommendation listand the You Might Like recommendation list are based on the timeslotdetermination of FIG. 12.

Referring now to FIGS. 13A and 13B, a list of the most watched channelsby timeslot is determined. Thus, a list of the channels in a rankedorder by count or other value such as a time watched value may beprovided corresponding to the most popular channels watched during aparticular timeslot. The channel list may include a channel identifierwhich corresponds to channels in the program guide.

In step 1310, the timeslot for analysis is determined. The timeslot foranalysis may be the current timeslot or next timeslot depending on thecurrent time relative to the end of the timeslot as described above inFIG. 12.

In step 1312, the watched program events from the viewer tracking logare obtained from previous days. The program identifier, channelidentifier, and the time watched for each of the programs are obtainedfrom the viewer tracking log. The time watched value is assigned in theviewer tracking log as set forth in step 1314. As will be describedbelow, the time watched value may be adjusted. In step 1316, it isdetermined whether the watched program event was a playback of arecording or a live program. In step 1316, if the program is arecording, the time watched value may be adjusted downward by anadjustment factor. The adjustment factor may be adjusted downward toaccount for the playback of recordings being less important than thelive viewings.

Referring back to step 1316, if the event is not a recording playback,step 1320 is performed. Step 1320 is also performed after step 1318. Instep 1320, it is determined whether the “watched program” event occurredon the same day of the week as the current day. If the watched programevent occurred on the same day of the week, the time value is adjustedupward in step 1322. Again, this may be another adjustment factor.

If the event did not occur on the same day of the week and after step1322, step 1324 determines whether the watched program event occurredgreater than X days ago. The value X may be set so that an adjustmentfactor may be used to reduce the value of old content. In step 1326, ifthe watched program event is greater than X days old, step 1326 adjuststhe time value downward by an adjustment factor. After step 1326, step1328 determines the overall time watched value for each channel. Theoverall time watch value of the values sum together and adjusted per theadjustment factors above.

After step 1328, step 1330 may perform the steps of 1312-1328 foradjacent timeslots. That is, the same analysis may be performed forfuture timeslots. This is an optional step. After step 1330, step 1332may adjust the time watched value for adjacent timeslots by anadjustment factor based on the time distance away from the currenttimeslot. Thus, timeslots directly adjacent to the current timeslot maybe adjusted downward less than slots two timeslots ago.

After step 1332, step 1334 determines the total adjusted time watchvalues for current and adjacent timeslots. A most watched channels listmay then be generated. Each element of the list may include a timewatched value. The list may be sorted by the time watched value with themost time watched being at the top of the list.

In step 1336, it is determined whether the total time watched value isless than Y. If the total time value is less than Y, the channel may bedropped from further analysis in step 1338. The value Y may be a valuechosen so that only significantly watched values are used. In step 1340,it is determined whether the channel watched time value is less than acertain percentage of the total watched time. This step is alsoperformed after step 1336. If the total watched time value is less thana certain percentage, step 1342 removes the channel from furtherconsideration. Referring back to step 1340, when the watched value isnot less than a certain percentage of the total watched time value. Step1344 sorts the channels with the highest total adjusted time watchedvalue. In step 1346, if there is a tie, step 1348 places the channelthat was most recently watched first in the list. Step 1350 is performedafter step 1348 and after step 1346 if no tie was found in the watchedtime value. In step 1350 a preferred channels list having channelidentifiers in an ordered manner based upon the time watched isgenerated. Various numbers of channels may be selected, such as the top10 channels. In step 1352, if the preferred channels list is greaterthan X channels, a timeslot viewer preferred list of channels isgenerated in step 1354.

In step 1352, if the preferred channels list is not greater than Xchannels, then step 1356 adds recommended channels from a recommendedlist to the preferred list. That is, the head end may generate arecommended channels list with default channels to use forrecommendations if no other information is available. These channels maylikely be the most popular channels determined by the user serviced bythe head end. The channels from the list may be screened so that thechannels received by the particular set top box or user device are used.The recommended list may include content in various categories and mayalternate the categories. For example, movie, sports, kids, newschannels may all be provided within the recommended channels list.However, one channel from each category may be provided at the top ofthe list so that the list may be varied in content. The recommendedchannels list may be communicated to the user device through variousmeans including channel objects communicated with the program guidedata.

Referring now to FIG. 14, a method for generating a list of relatedchannels to the timeslot viewer preferred list of channels is set forth.In step 1410, the timeslot viewer preferred channels list is generatedfrom FIG. 13. In step 1412, a list of related channels for each channelin the list is determined. A list of related channels may be determinedby descriptors provided with the program guide data for each channel.Fixed relationships between various channels may thus be provided anddetermined. The list of related channels includes channels that displaysimilar programs or channels that are commonly watched by viewers havingsimilar interests. In step 1414, the timeslot viewer preferred channelslist and the related channels list are combined into a combined relatedchannels list. In step 1416, the combined related channels list issorted by value or score. Each channel in the combined related channelslist is ranked or given a score value based on how related they are towhat is watched at the user device. In step 1418, a limited number ofchannels from the combined related channels list are used. For example,the top thirty channels may be provided in the combined list.

Referring now to FIG. 15, a method for determining what televisionseries have been watched during a specific timeslot is set forth. Theseries watched during a specific timeslot are referred to as a timeslotseries profile. The timeslot series profile includes the program orseries identifier. In step 1510, the viewing tracker log is analyzed tocount the watched program events on previous days during the timeslotbeing analyzed. The watched program events may include both programsviewed live or played back from the digital video recorder. In step1512, it is determined whether the program was a recording playback. Ifthe watched program event was a recording playback, step 1514 adjuststhe count or value associated with the watched program downward. In step1512, if the event was not a recording playback, step 1516 determines ifthe event was performed on the same day of the week. If the event wasperformed on the same day of the week, step 1518 adjusts the countupward. After step 1518, step 1520 is performed. Step 1520 is alsoperformed after step 1516 in which the event is now performed on thesame day of the week. In step 1520 it is determined whether the watchedprogram event was greater than X days ago. If the watched program eventis greater than X days ago, then the count may be adjusted downward byan adjustment factor in step 1522. It should be noted that theadjustment in step 1522 may be optional.

After step 1522 and when the watched program event is not greater than Xdays ago, step 1524 is performed. In step 1524, the program content fromthe same series is grouped together using the content identifier,content identifier type and/or the primary identifier or other indicatorof series. As mentioned above, the content identifier may have a seriesidentifier incorporated therein. In step 1526, the weighted count valuesfor each program in the group are summed together. The highest countvalues for a series having more than Y total programs, is generated.Thus, a timeslot series profile list having series that includes a typeof identifier such as a content identifier, a content type and a primaryidentifier is formed. The highest priority of content may be at the topof the list. It should be noted that if two or more series have the sametotal count value, the priority may be determined based on the positionof the series as specified in the prioritizer. This same total weightedcount value may also be prioritized by the most recently viewed seriescontent. It should also be noted that the time series profile isgenerated if the series generated is greater than two total programs. Aslong as there is more than two total programs within a series that havebeen watched, the timeslot profile series is generated in step 1530.

Referring now to FIG. 16, a method for determining a timeslot seriesprofile match is set forth. The timeslot series profile match attemptsto match currently airing programs or existing recordings to thepreviously generated timeslot series profile from FIG. 15. In step 1610,if recordings are found in the system, step 1612 is performed. Step 1612searches existing recordings for the content identifier matching thecontent identifier of the first content in the timeslot series profile.In step 1614, it is determined if more than one recording is found. Ifnot more than one recording is found, then the program content is addedto the What's On list. The title, content identifier or any other typeof identifier may be added to the What's On list in step 1616.

Referring back to step 1614, when more than one recording is found, step1618 attempts to select one of the recordings. In step 1618, the contentidentifier string may be used. In this specific example, the recordingwith the lowest secondary ID value which, in the present example, is thefourth number in the content identifier string is used in thedetermination. The recording with the lowest secondary identifier isused. In step 1620, if there is not greater than one value, the lowestsecondary ID value is added to the list in step 1616. If there is stillgreater than one recording, step 1622 adds the content from the higherchannel to the What's On list. Of course, steps 1618 and 1622 arearbitrary ways for resolving the conflict in the list.

If no recordings were found in step 1610, step 1630 is performed. Inthis case, the most watched channels by timeslot determined in FIG. 13are utilized. In step 1632, it is determined whether the currentlyairing program on that channel has a content identifier matching thefirst three values as those in the content identifier for the firstseries in the timeslot profile. If it does, step 1616 adds the currentlyairing program to the What's On list. In step 1632, if the currentlyairing program does not match What's On the timeslot profile in step1634, the next channel in the most watched channels list is used in step1636. After step 1636, step 1632 is repeated.

Referring back to step 1634, when the currently airing program doesmatch the timeslot profile, it is determined whether the currentlyairing program on any channel matches the content identifier from thelist in step 1638. After step 1638, if more than one match is not foundin step 1640, step 1616 adds the currently airing program to the What'sOn list. In step 1640, if more than one match is found, the secondaryidentifier or the most recent start time or the highest channel numbermay be used to resolve the conflict in step 1642. This step may performsteps similar to steps 1618-1622 described above.

Referring now to FIGS. 17, 18 and 19, some of the above-mentionedmethods refer to genre-matching. In FIG. 17, genre-matching is describedin further detail. Genre-matching uses category weighting to represent auser's taste based upon their previously watched programs. In thismethod, the recommendation engine ranks programs by applying acalculation to each candidate program and returning the programs bypriority based on the value returned for the calculations. The programsare then ranked highest to lowest based on the calculation of each valuefor each program. In general, the calculation is derived against theprogram genres from the APG object category description. The calculationadds a weight for each category index found in the candidate program andthe sum represents the program's cosine similarity with the user's genreprofile. In step 1710, a genre profile target vector is determined. Thegenre profile target vector is learned over time based on watchedprogram events. The genre profile target vector may be adjusted on thefly as new watched program events occur. A genre profile target vectormay be adjusted for all watched programs or a separate target vectorthat applies each timeslot may be adjusted only when programs arewatched in the time-slot. In FIG. 18, a simplified two-dimensionalrepresentation of comedy and action is illustrated. However, in anactual implementation, multiple vectors with multiple characteristicsmay be used. In this example, the target vector T1 is a unit vectorwhich equals (0.5, 0.87) as its components. The target vector T1 iscompared to a candidate program. The categories of the candidate programare obtained in step 1712. In FIG. 18, vector C1 represents action,comedy and vector C2 represents comedy, while vector C3 representsaction. Each candidate program vector is a unit vector having categoryweights equal the inverse square root of the number of categories.

In step 1714 the cosine similarity is calculated. The cosine similarityis a measure of the closeness of a candidate program vector to the genreprofile target vector. The dot product between the candidate unit vectorand the target unit vector is equal to the cosine of the angle betweenthese vectors. The dot product is calculated by adding the categoryweights of the target vector for each category in the candidate program.The sum of weights is divided by the square root of the number ofcategories. This genre match calculation is illustrated in FIG. 19. InFIG. 19, a table having category vectors in the first column, action inthe second column, comedy in the third column, and cosine similarity isset forth. The target vector T1 has a value of 0.5 for action and 0.87for comedy. It should be noted that these values represent a normalizedunit vector. Candidate C1 has an action value of 1 over the square rootof 2 and a comedy value of 1 over the square root of 2. Candidate C2 hasan action value of 0 and a comedy value of 1 and candidate C3 has anaction value of 1 and a comedy value of 0. Thus, the cosine similarityof each is 1, 0.97, 0.87 and 0.5 respectively. The angle of the cosineis in parentheses in the cosine similarity column. The closest vectorwill have the highest cosine value and thus the second row candidate C1has the lowest angle and thus is the most similar. Essentially, thecosine similarity represents the closeness of the vectors. The actualangle need not be determined since the closest to the number 1 is theclosest in cosine similarity. The cosine between the two unit vectors ofthe target T1 and C1, C2 and C3 is derived from the dot product of thevalues in the vectors.

In FIG. 17, step 1716 determines the angle from the target vector.However, as mentioned above, the closeness of the target vector to acandidate vector is determined by the cosine values and may not requirethe determination of the actual angle. In step 1718, the list ofcandidate programs relative to the angle of the vector or the closenessof the target vector is set forth.

Referring now to FIGS. 18, 20 and 21, the correction value may beobtained when a new program is watched in 2110, a weight correction oftarget vector T1 illustrated in FIG. 18 is obtained. The new targetvector is target vector T2. The table illustrated in FIG. 20 illustratesan example target vector with various genre weights in four differentcategories, with initial weights 0.13, 0.67, 0.72 and 0.12 respectively.If a program is viewed which has only categories with category index 1,2 and 4, but not 3, the genre match result of the viewed program is thesum of the weights for all existing categories in the program divided bythe square root of the total number of categories. In this case, ifcategories 1, 2 and 4 are used, the result is 0.13 plus 0.67 plus 0.12divided by the square root of 3 which equals 0.53. The value 0.53 is agenre match value.

The weight in the target vector is adjusted to new weight to incorporatefeedback from recently watched programs. The new weight equals the oldgenre weight plus the step size divided by the square root of the numberof categories in the program multiplied by the normalization value minusthe genre match calculation of the program. For example, if the stepsize is 1, the weight adjustment is 1 minus 0.53 divided by the squareroot of 3. The resulting value 0.27 is the adjustment for the genreweights corresponding to the viewed program. Thus, if the program havingthe weights illustrated in FIG. 20 were used, the new category indexesof 1, 2 and 4 are adjusted to 0.4, 0.94 and 0.39, while category 3remains 0.72. The adjusted weights are also shown in FIG. 20. The lengthequals the square root of the sum the genre weights squared. The newlength equals 1.31. One divided by the new length is then multiplied byeach category index weight to obtain the new normalized weights. The newtarget vector comprising the normalized weights for the four categorieschanges to 0.31, 0.72, 0.55 and 0.30, respectively.

Referring back to FIG. 21, the genre weights for each of the category ofthe new program watched is adjusted based upon the weight correction asdescribed above in step 2114. In step 2116, the weights in the genreprofile are adjusted. The weights are then normalized by dividing by thelength as described above in step 2118. The genre match calculationdescribed above corresponds to a cosine similarity error measurement,and the weight adjustment corresponds to a stochastic gradient descent,but many other genre matching or weight adjustment algorithms may beused.

Referring now to FIG. 22, a use case is presented in which the set topbox or user device has stored the viewing history illustrated in theviewer tracking log over the last 36 days. In this example, a viewerthat is using the user device asks for recommendations at a time when henormally watches a particular series. As can be seen in the figure, atitle column, a content identifier column, a channel column, a datecolumn which gives the relative date of the content, a timeslot columnand a watched time column are illustrated. Each of the titles thus haseach one of the different types of data in each of the columnsassociated therewith. Also in the following example it is presumed thatthe recommendation request is performed at 7:12 p.m.

Referring now to also FIG. 23, the program guide includes the data inthe table. The program guide data may include the title, a contentidentifier, a channel, a date, start time and duration. Each of thetitles has each of the data from each of the columns associatedtherewith. Data has also been provided for related episodes whichincludes the Simpsons episode content identifier 11 20 8 which is linkedto the Family Guy episode 11 46 17. In the following case, the timeslotto be used is the 7:00 p.m.-7:30 p.m. timeslot. By applying the abovemethods, the timeslot series profile returns Seinfeld and the Simpsons.The series are identified in this Example as the first four digits beingthe same. (Simpsons, 1 1 20, Seinfeld 1 1 10). The viewer preferredchannels are 217, 216, and 705. The first timeslot profile seriesmatches an episode currently airing on a channel list in the mostwatched channels by timeslot list so that Seinfeld on channel 217 at7:00 p.m. is added to the What's On results list. The second timeslotprofile series does not match an episode on any channels in the mostwatched channels by timeslot list but, does match a currently airingprogram on channel 215. Therefore, the Simpsons on channel 215 at 7:00p.m. is added to the What's On results list.

The currently airing program on the second channel in the most watchedchannels in the timeslot list has not been added so, based on a genrematch ranking, Futurama on channel 216 at 7:00 p.m. is added to theWhat's On results list.

The currently airing program on channel 705 is the only other programnot added yet. The programs on the other two channels have already beenadded. Therefore, golf on channel 729 at 6:00 p.m. is added to theWhat's On results list.

For the You Might Like list, the data link for the Simpsons refers tothe Family Guy on channel 306 so that the Family Guy is added to the YouMight Like results list. All upcoming programs for up to three hours maybe obtained from the related channels list generated from theviewer-preferred channels list. Presuming the following match the genrematched test, there are only three shows that have not passed or beenadded to the What's On list or the You Might Like list. These areNightly News on channel 217 at 7:30 p.m., Futurama on channel 216 at7:30 p.m. and Sports Center on channel 729 at 9:00 p.m. These resultsmay be sorted chronologically so that nightly news, Futurama, SportsCenter and The Family Guy are presented in that order. A screen displayhaving posters or thumbnails and/or alphanumeric characters may be usedfor presenting the What's On and You Might Like lists.

Referring now to FIG. 24, the recommendations for a new set top box donot take into consideration previously watched programming. In thiscase, a recommendation is requested by the user at 7:12 p.m. The data inFIG. 24 is within the program guide. In this example, it is alsopresumed that the Simpsons episode with a content identifier equal to 11 20 8 links to The Family Guy episode content identifier equals 1 1 4617. It is also presumed that no daily editorial lists are defined. Therecommended channels list includes in this order: channel 216, channel217, channel 215, channel 710, channel 340, channel 450, channel 729,channel 1007, and channel 1005. Five programs are selected thatcorrespond to the programs on the recommended channels list. In theproper order, Futurama on channel 216, Seinfeld on channel 217, theSimpsons on channel 215, Psyche on channel 710 and golf on channel 729are returned. The genre match algorithm is applied to each program andassuming that they all pass except for Seinfeld on channel 217, theWhat's On list will result in Futurama, the Simpsons, Psyche and golfall being returned in that order.

The You Might Like list uses a related data link which, as mentionedabove, links the Simpsons to The Family Guy. The related channels listultimately gathers only three programs because they are the only currentand future programs left airing on any channel of the recommendedchannels list. The following three programs, Seinfeld, House and SportsCenter are added to the You Might Like list. Chronologically, the listmay be sorted as Seinfeld, House, Sports Center and The Family Guy.

Referring now to FIG. 25, a method for communicating a recommendation toa user device is set forth. In step 2510, a marketing list is generated.The marketing list may be generated within the head end 12. Themarketing list may be an ordered list of content or content identifiersthat has been placed in a particular order by a marketing specialist.The order may represent a priority order. In one example, the marketinglist may have a score or level associated therewith. In another examplethe marketing list may be categorized. For example a mandatory categorymay be provided. The mandatory category may be the highest priorityprogram to be recorded. The order of the mandatory programs may bedetermined by their order on the marketing list. Mandatory programmingmay apply to all user devices.

Another category may be a targeted program category. This secondcategory is below the first category of mandatory programs in terms ofpriority. Amongst them the targeted program category list may bedetermined by a calculated probability value. The determination of theprobability is set forth below. In short, the probability is determinedwithin the set top box or user device. The targeted programs may applyonly to user devices with a viewing history that pertains to thetargeted programs.

Another category set forth within the marketing list is an optionalprogram. The optional programs have a lower priority than the targetedprograms and the mandatory programs. Amongst themselves the optionalprograms is determined by their order in the marketing list. Theseprograms apply to all user devices.

Referring now to FIG. 26, an example of a marketing list is set forth.In this example the first column 2610 indicates the type set forthabove. Examples of mandatory, targeted and universal/optional are setforth. The marketing list may also include an identifier for thecontent. In this example the identifier is a tribune media systemidentifier set forth in column 2612. Each content title has a uniqueidentifier. Each content may also include a title which is includedwithin the column 2614. Although only seven titles are shown in themarketing list, tens or hundreds of titles may be included therein.

Referring back to FIG. 25, after the marketing list is generated in step2510, step 2512 generates a related program list. The related programlist may also include a strength of similarity therewith. The strengthof similarity is a related score. The related program list is used togenerate the relationship needed for the targeted program for therecommended recorded list. The relationship allows the user device toeasily determine if a candidate targeted program is applicable to aparticular user device by comparing the user devices viewed programs tothe related programs of the candidate target program. This is a list ofpossible programs to record if there is a match to at least one of itsrelated programs.

Referring now to FIG. 27, a related program list is illustrated. In thisexample, a program column 2710 includes various programs. Relatedprograms are set forth in column 2712. The related programs may begenerated automatically, by a marketing employee or a combination of thetwo. Column 2714 illustrates a weighted score that corresponds to astrength of similarity for the related programs. In this example,Seinfeld had a weighted score of 89 in relation to the program ThirtyRock. “Seinfeld” and “Parks and Recreation” had a weighted score of 75in relation to the program Thirty Rock. Of course, various numbers ofrelated programs and weights may be used.

An external service may also be used in the formation of the relatedprograms list. For example, the commercial service VTAP may be used. Ofcourse, other types of commercial services may be available forproviding related programming.

Referring back to FIG. 25, step 2514 generates an externalrecommendation and list with content identifiers. This may also bereferred to as an aggregated list. The external recommendation list mayinclude the marking list, the related program list as well as a programguide schedule for a predetermined amount of time such as two weeks. Theexternal recommendation list may also be influenced by outside sourcesincluding a ratings source. Various types of rating sources may be usedto influence the external recommendation list in both the order andcontent of the list. Ratings providers may include Nielsen® and BlueFin®. The ratings providers are illustrated in box 2516. A “What's Hot”list generated by the service provider may also be used to influence theexternal recommendation list. The “What's Hot” list is generated by theservice provider to correspond to the most watched and most popularitems. In this example the “What's Hot” list 2518 is generated withinthe service provider of the head end 12. As mentioned above. The futureprogram guide schedule 2520 may also be provided with or influence theexternal recommendation list. After the external recommendation list isgenerated, step 2522 provides a review of adjustment of the externalrecommendation list.

In step 2524 the external recommendation list is converted to binary toform a recommendation binary format data file. In step 2526, the binaryformat data files are encapsulated into payload objects. In this examplethe use of payload objects is a known method for communicating programguide data. In this example, in addition to program guide data, thepayload objects may be used to communicate binary format data files. Instep 2528 the payload objects are communicated to the user devices.

Referring now to FIG. 28, a method for generating a most viewed serieslist is set forth. In step 2810 a user device generates a viewer eventin response to a program being viewed. The viewer event for the programviewed is stored in a viewer tracking log having a time viewed. Theviewer event may be received by the user device in various predeterminedincrements such as every half hour as described above. In step 2812 thenumber of episodes for a series is used to form a series count list. Instep 2814 the series count is adjusted by the amount of time viewedwithin the half hour. In step 2816 the series count may be adjusted downbased upon the last time and since the last viewing of the series. Thus,if a series is not watched for several weeks, the count may be adjusteddownward. If the series is watched on a regular basis the series countmay be maintained. In one example a reduction of 9% of the series countfor every thirty days not viewed may be used. In step 2818 the seriescount is monitored for each of the series in a series count list. Instep 2820, if the series count is less than a predetermined threshold,step 2822 removes the series from the series count list.

Referring back to step 2820 when the series count is not less than thepredetermined threshold the system returns to step 2810. In a systemthat includes multiple user devices, the viewing history of all of theclients within the local system may be aggregated in the most viewedseries list. Alternatively, the individual user devices may haveseparate series lists.

Referring now to FIG. 29, a method for storing content in a user deviceis set forth. In step 2910, the external recommendation list is receivedfrom the payload object. In this example the payload objects arereceived from the satellite. Other systems may receive the payloadobjects from the network 36 illustrated in FIG. 1. That is, the payloadobjects may also be received through a broadband or other type ofnetwork.

In step 2912 the most viewed series list having a series count isdetermined. In this example the most viewed series list having a seriescount may be determined at a home media center. This process wasdescribed above in step 2812.

In step 2914, the external recommendations list is compared to the mostviewed series list. The items may be compared on an entry by entrylevel. In step 2916 if a match is not determined, step 2914 proceedsuntil each of the external recommendations list is compared to the mostviewed series list. When matches are determined in step 2916, step 2918determines the probability of correlation of external recommendationslist and the most used series list. This may be performed on a periodicbasis such as once every night.

In step 2920, a recording recommendation list based on the probabilityof various items of the list is generated. This process may be initiatedby the recommendations module requesting content to be recorded and maybe performed periodically such as every thirty minutes. Therecommendation engine may request up to a predetermined number ofcontent titles for recording in any timeslot. In step 2922 when theitems are universal items within the recording recommendation list, theitem's start time and end time are determined. The item's channel valuesmay be used to narrow the search. In step 2924, the list item isdetermined whether it's a mandatory universal item or an optionaluniversal item. A value may be assigned based upon whether the editorialsubtype is mandatory or optional. In step 2926 is determined whether theitem in the list is a targeted item. The probability value may be zero.In step 2928, the guide data is used to determine the start time and endtime values as well as the channel values for the targeted item. If amatching item is found in the time period of interest the targeted itemis added to the recommended recording list. In step 2930 the recommendedrecording list is ordered. In this example the mandatory/universal itemsare first. These items may be placed in the recording recommendationlist by position in the editorial list. Next, targeted items may beordered by calculated probability. Optional items may be positioned lastin the editorial list. In step 2932 the predetermined number ofrecording recommendations is returned to the middleware of the userdevice.

In step 2934, it is determined whether the returned items are alreadyprescheduled. If the items on the list are prescheduled by a userpreviously requesting the items, the recording is not scheduled twiceand is thus removed from the recording recommendations. In step 2936 thetuner availability is determined. The maximum number of program contentthat may be recorded depends upon the available tuners. Tuners may beused for watching live content as well as recording requested contentfrom the user device. Watching live content and recording contentrequested by a user through a user interface or the like has higherpriority than content recorded automatically. In step 2938, therecording is scheduled based upon availability and the prescheduleditems. In step 2940, the content is recorded and stored within a memoryof the user device. Further details of the recording process areprovided below.

Referring now to FIG. 30, a home media center 50 is illustrated. In thisexample, a front panel 3012 is illustrated having various controlsincluding a selector 3014 for providing a user interface for selectingvarious content and moving cursors on a screen display. Indicators 3016indicate the resolution of the content being received. A guide indicator3018 indicates the guide is being viewed. A menu indicator 3020indicates that a menu is being displayed. A recording indicator 3022 isilluminated to indicate content being recorded within the user device.As will be mentioned below, the recording indicator 3022 may beilluminated when the user device is recording. However, the recordingindicator 3022 may also be suppressed when content from the recommendedrecording list is being recorded. Because the content from the recordingrecommendation list is very low in priority, by not illuminating therecording illuminator, the user will think the user device is availableto record recordings or tune to a live program. Because of the lowpriority of recording recommendation list content, the recordingrecommendations will be stopped upon user interaction for the use ofanother tuner.

Referring now to FIG. 31, a screen display 3110 illustrating a memoryspace indicator 3112 is set forth. The memory space indicatorcorresponds to the available memory capacity available within the userpartition. In this example, the memory space indicator 112 has a usedportion 3114 indicating 75% available space. An unused capacity portion3116 illustrates 25% available space. As will be described below theamount of space available may not include the recording recommendation.Thus, the unavailable space includes the content requested specificallyby the user. The recommendation recordings are included within theunused capacity 3116. That is, the memory space associated with thecontent recorded from the recording list is not shown in the memoryspace indicator.

Referring now to FIG. 32, a method for storing content within the userdevice is set forth. As mentioned above the user device may be in settop box 22, a home media center 50, or another type of media devicewhich is a mobile device 40 as illustrated in FIG. 1. In step 3210 therecording recommendation list is generated as described above. In step3212 a tuner of the user device is tuned to record the first content.That is, the content list may have various information associatedtherewith so that the channel, time and other recording information maybe determined.

In step 3214, the content from the recording list is stored in the userpartition to form stored content. In step 3216, the user device is tunedto select live content. This may be performed by the user using a remotecontrol device to tune to a predetermine channel. A remote controldevice is one example of an interface for tuning to live content.Control buttons on the user device itself may also be used as the userinterface. Content may be selected from a graphical user interfacedisplayed on the screen display. This includes the program guide as wellas a user interface that displays recommendations from the live content.Such a user interface may be referred to a “What's On” user interface.

In step 3218 it is determined whether the selected live content in step3216 corresponds to content that has already been stored in the userdevice. Such content may be fully stored or partially stored. The usermay tune to the content after the content start time. The user devicemay be recording the content automatically because the content may be onthe recording recommendation list. If the selected live content isstored content step 3220 generates a screen display query for accessinga previous position of the stored content. For example, the screendisplay may ask the user if the user would like to restart the contentfrom the beginning position or another previous position. This may bereferred to as a restart query. If answered affirmatively, a restartsignal may be generated by the controller. In step 3222, if a previousposition or restart was selected the previous stored content isretrieved from the user partition in step 3224 in response to a restartsignal. Thereafter, the stored content is played back from the selectedposition in step 3226.

Referring back to steps 3218 and 3222, when either of these steps isanswered in the negative, the live screen may be displayed from thetuner in step 3228.

Referring now to FIG. 33, multiple content may be stored in the userdevice. As mentioned above, content may be stored under user request forautomatic from the recording recommendation list. In step 3312, therecording indicator is suppressed when recording content from therecording recommendation list is set forth above. The content may berecorded in the user partition of the user device.

In step 3314 when a disc space screen display is selected step 3316available user space may be determined by adding recommendationsrecording space and the user partition space. The disk spaceavailability is typically determined for only the user partition portionof the memory. In this example the user partition availability isdetermined by subtracting the user requested content from the overallavailability. The recommended recording content space is not included inthe memory space available. In step 3318 the available partition spaceis displayed to the user.

Referring back to step 3314, if the disk space availability is notrequested step 3310 is again performed.

Referring now to FIG. 34A, a screen display 3410 for introducing therecommendations is set forth. In this example a What's On portion 3412illustrates content that corresponds to recommendations that arecurrently being broadcasted these may be provided in posters. In thisexample only four posters are illustrated. Underneath each postervarious identifiers may be provided including the channel name. Inaddition, two of the posters have a recorded indicator 3416 thatcorresponds to contents stored within the user device. Screen displayportion 3418 invites the user to select the automatic recording feature.

Referring now to FIG. 34B, a recommendation initiation screen 3430 isset forth. An affirmative answer to the screen display 3432 selects theservice and allows the user device to begin recording contentautomatically.

Referring now to FIG. 35, user interface 3510 includes a What's Onportion 3512 and a recommended recording portion 3514. The content inthe portion 3514 is content that is either fully or partially recordedwithin the user device. As mentioned above, the recommended recordingsmay be stored in a user partitions. Recording indicators 3516 may beused to indicate the content is stored in the user device. The contentin the What's On portion 3512 was described above.

Referring now to FIG. 36, a screen display 3610 is obtained when theposter for the corresponding program was selected from the recommendedportion 3514. In this example, the highlighted portion 3612corresponding to the “entertaining” episode of Mythbusters is set forth.But programming language is also set forth. Under the selection box 3612are related recommendations 3614. These may be selected by the user at afuture time. Repeats of the same episode are shown by the channels “2”and “391” in the fourth column. Either show may be chosen by the userfor future recording.

Referring now to FIG. 37, after one of the episodes has been selectedthat corresponds to the content recommendation, a screen display 3710asking the user if a series should be recorded by the query box 3712.The query box includes the answer to the question “Do you likeMythbusters?” The query box includes yes, record the series; no, removethe series or do nothing. If the series selector 3714 is selected thenevery content instance of the series will be recorded in the future.Duplicates may be excluded

Referring now to FIG. 38, an expanded screen display 3810 illustratingrecommended recordings is set forth. In this example, the recommendedrecording list 3812 having recording list content has been expanded. Itshould be noted that the recorded indicator 3814 illustrates that eachof the contents have been recorded. A cursor 3816 may be selected andmoved to select a particular recommendation. As mentioned above, therecommendations are for a predetermined time period.

Referring now to FIG. 39, a screen display 3910 is illustrated. In thisexample the poster for “Mythbusters” has been selected in FIG. 38. Inthis example an episode list 3912 is retrieved for all the contentstored for the same series. By selecting one of the content titles, thecontent may be viewed on the screen display. The series may also bedropped from the recommendation list by the selection box 3914.

Referring now to FIG. 40, a screen display 4012 is illustrated for aconfirmation selection for removing the series from the recommendationlist. In this example, a series choice of “yes” or “no” is illustratedin the query box 4014. A selection of “Yes” removes all of the episodesof a series from the recording recommendation list. A selection of “No”keeps the series within the recommendation list.

Referring now to FIG. 41, a screen display 4110 generates a confirmation4112 that the series has been removed from the recommendation list. Toproceed, the user is prompted through a user prompt 4114. In thisexample, the user prompt is “okay” to proceed.

Those skilled in the art can now appreciate from the foregoingdescription that the broad teachings of the disclosure can beimplemented in a variety of forms. Therefore, while this disclosureincludes particular examples, the true scope of the disclosure shouldnot be so limited since other modifications will become apparent to theskilled practitioner upon a study of the drawings, the specification andthe following claims.

What is claimed is:
 1. A method comprising: receiving an externalrecommendation list to a user device, said external recommendations listcomprises a marketing list comprising a plurality of marketing listentries and a related program list comprising a plurality of relatedprogram entries that are related to the plurality of marketing listentries, each marketing list entry comprising a related scorecorresponding to a respective marketing list entry; generating a mostviewed programming list at the user device; comparing the externalrecommendations list and most viewed programming list using the relatedscore; generating a recommended recording list in the user device usingboth the external recommendation list and the most viewed programminglist; and storing at least one content from the recording recommendationlist at the user device.
 2. The method as recited in claim 1 whereingenerating the external recommendation list comprises generating theexternal recommendation list in response to viewer rating.
 3. The methodas recited in claim 1 wherein generating the external recommendationlist comprises generating the external recommendation list in responseto a marketing list.
 4. The method as recited in claim 1 whereingenerating the external recommendation list comprises generating theexternal recommendation list comprising recommended content.
 5. Themethod as recited in claim 1 further comprising suppressing the step ofstoring when the content is already stored in the user device.
 6. Themethod as recited in claim 1 wherein generating the most viewedprogramming list comprises tracking viewer events within a user deviceto form a viewer tracking log.
 7. The method as recited in claim 6wherein generating the most viewed programming list comprises generatinga series count list having a series count based on the viewer trackinglog.
 8. The method as recited in claim 7 further comprising adjustingthe series count based on a time period since a last viewing.
 9. Themethod as recited in claim 7 further comprising adjusting the seriescount based on a time viewed for a series.
 10. The method as recited inclaim 7 wherein generating a recommended recording list comprisesgenerating the recommended recording list based on the series count listand the external recommendation list.
 11. A user device comprising: amemory; and a controller storing an external recommendation list in thememory, said external recommendations list comprising a marketing listcomprising a plurality of marketing list entries and a related programlist comprising a plurality of related program entries that are relatedto the plurality of marketing list entries, each marketing list entrycomprising a related score corresponding to a respective marketing listentry; said controller generating a most viewed programming list,comparing the external recommendations list and most viewed programminglist using the related score and generating a recommended recording listusing both the external recommendation list and the most viewedprogramming list; said controller storing at least one content from therecording recommendation list in the memory.
 12. The user device asrecited in claim 11 wherein the external recommendation list is formedin response to a viewer rating.
 13. The user device as recited in claim11 wherein the external recommendation list comprises a marketing list.14. The user device as recited in claim 18 wherein the externalrecommendation list comprises recommended content.
 15. The user deviceas recited in claim 11 wherein the controller suppresses storing whenthe content is already stored in the memory.
 16. The user device asrecited in claim 18 wherein the controller generates the most viewedprogramming list comprises tracking viewer events to form a viewertracking log.
 17. The user device as recited in claim 11 wherein themost viewed programming list comprises a series count list having aseries count based on the viewer tracking log.
 18. The user device asrecited in claim 17 wherein controller adjusts the series count based ona time period since a last viewing.
 19. The user device as recited inclaim 17 wherein the user device adjusts the series count based on atime viewed for a series.
 20. The user device as recited in claim 17wherein the user device generates the recommended recording list basedon the series list and the external recommendation list.